Tree community overyielding during early stand development is explained by asymmetric species‐specific responses to diversity
Bibliographic record
Abstract
Abstract Recent long‐term tree biodiversity experiments have shown that diversity effects on productivity tend to strengthen over time, as complementarity among constituent species increases over the course of forest development. However, these community‐level metrics only account for the net outcome of multiple interactions among species and, thus, do not inform about the individual species' responses to diversity. In this study, using 11 years of growth records from a large diversity experiment, we explored how species respond to diversity based on their functional traits and those of their heterospecific neighbours over time and analysed their contribution to the community‐level overyielding. We show species‐specific responses to diversity, with fast‐growing deciduous species rapidly performing better in mixtures relative to monocultures, than slow‐growing evergreen species. Moreover, we find that species productivity in mixtures enhances over time as the proportion of slow‐growing evergreen species in the heterospecific neighbourhood increases. These patterns of response of species scale up and explain community overyielding, which occurs primarily in deciduous‐evergreen mixtures and is explained by the overyielding of deciduous species overcompensating the poor performance of evergreen species. This study sheds light on the temporal dynamics of species responses to diversity, which together help improve our understanding of community‐level overyielding over the course of stand development. Read the free Plain Language Summary for this article on the Journal blog.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".